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This site is dedicated to the ADAT toolbox

The treatment and handling of large
quantities of time series sensor data is a particular challenge for the sport
science community. Significant quantities of data can be generated during
routine training sessions that involve multi-sensor monitoring on multiple limb
segments. Whilst sensor devices are commonplace, the data formats, available
sensors and acquisition rates vary considerably. Additionally sensor fusion is
of increasing intrest where multiple data sets from multiple sources are
required to be combined.

In this paper we present a set of
tools that have been developed over the last 5 years to help meet this emerging
challenge. The tools are based on the popular computational environment Matlab,
which allows rapid customisation of routines, together with complex analysis
and visualisation tools to be used by technical and non-technical researchers
alike. Using these developed tools data gained from a variety of sources
(including video) can be combined together, visualised and processed using over
50 processing and visualisation tools.

The toolbox is designed to
automatically annotate data sets to keep track of signal processing steps and
maintain original data source integrity. It can also be easily extended and
customised for individual applications. At its core is the ‘athdata’ data
structure, which can accommodate multiple channels and kind of data at a
variety of sample rates, annotations and unlimited processing steps. A sample
import tool has been developed for users to easily apply the toolbox to their
own data sets and real-time streaming of data into the toolbox is also
possible.

When adopted as a
research team tool it facilitates the sharing of developed processing and
visualisation steps, it also enables a faster path to application for new
researchers joining any team